Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.
We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.
Groups & Labs
Interactive Data Lab
The Interactive Data Lab aims to enhance people’s ability to understand and communicate data through the design of new interactive systems for data visualization and analysis.
RAIVN Lab
The Reasoning, AI, and VisioN (RAIVN) Lab directed by Prof. Ali Farhadi and Prof. Ranjay Krishna focuses at the intersection of computer vision, machine learning, natural language processing and robotics and is targeted towards helping computers…
Allen School Faculty
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Centers & Initiatives
MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.
TCAT harnesses the power of open-source technology to develop, translate, and deploy accessible technologies, and then sustain them in the hands of communities. Housed by the Paul G. Allen School for Computer Science & Engineering, TCAT centers the experience of people with disabilities as a lens for improving design & engineering, through participatory design practices, tooling and capacity building.
Highlights
Allen School News
Itani, who works with Allen School professor Shyam Gollakota in the Mobile Intelligence Lab, was recognized for exceptional early-career research advancing AI systems for “superhuman” hearing.
HearingTracker
A technology known as semantic hearing developed in Allen School professor Shyam Gollakota’s lab could let users create acoustic bubbles, isolate chosen voices, and control individual sounds in their environment.
MIT Technology Review Korea
Allen School professor Su-In Lee discusses the role of artificial intelligence in science and medicine and explains why the process the model follows to arrive at an answer is as important as the answer itself.